Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$18
per month per host
Firebase
Score 8.2 out of 10
N/A
Google offers the Firebase suite of application development tools, available free or at cost for higher degree of usages, priced flexibly accorded to features needed. The suite includes A/B testing and Crashlytics, Cloud Messaging (FCM) and in-app messaging, cloud storage and NoSQL storage (Cloud Firestore and Firestore Realtime Database), and other features supporting developers with flexible mobile application development.
$0.01
Per Verification
New Relic
Score 7.9 out of 10
N/A
New Relic is a SaaS-based web and mobile application performance management provider for the cloud and the datacenter. They provide code-level diagnostics for dedicated infrastructures, the cloud, or hybrid environments and real time monitoring.
$0
No credit card required; 100 GB free ingest per month, 1 free full user + unlimited basic users, 8 days retention, 100 Synthetics Checks
Pricing
Datadog
Firebase
New Relic
Editions & Modules
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
Phone Authentication
$0.01
Per Verification
Stored Data
$0.18
Per GiB
Free (Forever)
$0
No credit card required; 100 GB free ingest per month, 1 free full user + unlimited basic users, 8 days retention, 100 Synthetics Checks
Telemetry Data Platform
$0.25
per month per extra GB data ingest (after first free 100GB per month)
Incident Intelligence
$0.50
per month per event (after first 1000 free events per month)
Standard
$99
per month per full user (after first free full user - unlimited free basic users)
Pro
Contact sales team
Enterprise
Contact sales team
Offerings
Pricing Offerings
Datadog
Firebase
New Relic
Free Trial
Yes
No
No
Free/Freemium Version
Yes
No
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
Datadog has been harder to setup out-of-the-box compared to its alternatives, although it's graphs and dashboards have been more useful. Other tools handle individual tasks better. For example, Splunk has been the best logging tool I've used, and New Relic is great for CPU and …
New Relic was a good tool but had really pushy salespeople. They also released a product called infrastructure recently, and it was worse than their previous product (servers). The previous product was also free! Needless to say, we will not be going back to New Relic any time …
We've completely replaced New Relic with Datadog and find it easier to use and more comprehensive. Our AWS and Sentry usage will continue for now. But Datadog gives us a much broader coverage - we can monitor our AWS services and many other services that interact with them. …
ease of use and implementation, other than New Relic (which I think is terrible in every possible way), the other two support opentelemetry better, have more manageable costs and comparable basic services, but they do not have the breadt of services dd does.
Datadog seems to be the most feature-rich of all the alternatives we've considered, however due to problems outlined earlier, some of the others have benefits. OpenTel can give us a way to make our platforms compatible with a variety of vendors, and can be done without …
Datadog has reliable monitoring with deep insights and straightforward integrations.
Verified User
Director
Chose Datadog
I use Datadog because it concentrates all these features into a single tool, facilitating the learning curve that my platform and development engineering team needs in order to be able to set up the monitors/alerts/SLIs/SLOs as well as to diagnose a production issue. Its easier …
UI of the Datadog is easy to understand and integration steps are easy to understand. It also provides the troubleshooting steps which are easy to understand. Supports multi cloud integrations which is very important for all the customers to know about the cloud service's …
Verified User
Engineer
Chose Datadog
I selected Datadog because of its features and the wide range of integration support. As I already told it supports more that 600+ integrations which helps and organization to keep everything in a single place and also its AI feature which is reducing the time for root cause …
1. Grafana is good, but a lot of integration is required for it to work. .that not the case of Datadog 2. Faster to set up Datadog instead of Grafana 3. Alerting in Datadog feels much easier thanin Grafana.
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.
Datadog crushed the competition on price and offering more solutions in one product cutting down on implementation time and effort while ensuring that the "integration" between one of their offerings was completely compatible with any of the others. I'm sure it's not the case …
It's a one-stop solution for all our needs whereas in other open-source tools, we have an operational overhead to keep and manage the uptime of these tools as well and also manage their versioning, upgrade, and patching cycle. Also if there are any bugs then we have to raise an …
One of the most important reason is single agent configuration for all kinds of monitoring. It also proved an auto upgrade feature of agents that reduces the overhead. It also provides range of options when it comes to data visualization and dashboards. It also provide tagging …
It has been easier to work with Datadog for all our business needs and get things on their roadmap if we found it lacking. Currently we use a mix of various tools as they were existing prior to Datadog came. We are evaluating new offering like Datadog's latest log management to …
We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.
Firebase is well suited for projects with simpler database workloads that require its real-time features. For data that is heavily read in real time, it's a great choice and gives developers a lot of features that would have been complicated and time-consuming to build up front …
I prefer New Relic over Datadog. I like their dashboard and I'm used to how it works in general. The price for Datadog is lower though, which makes the company consider it from time to time.
There's nothing like New Relic. pingdom has an APM module but it lacks the detail of New Relic. Datadog's strength is measuring the hosting infrastructure rather than the app itself. Sometime you need APM to see what your app is doing.
New Relic's APM is better than Datadog's. It has better traces and dashboards. The Apdex-based alerts are accurate and work predictably even at a large scale. However, New Relic can become expensive as the volume of data ingested grows. Datadog has better dashboards and …
Less expensive than Datadog and Sentry with almost everything we need. Less effort to set up and maintain than elastic search and kibana so saved a ton on engineering bandwidth which would have otherwise been lost.
New Relic continuously focusing on Open Telemetry and agentic AI integrations which is helping users to focus on the latest technology and as we all know that in future Observability will be mostly on OTel concept and AI driven and New Relic focusing on those area. Apart from …
The main reason is its pricing models which is value for money with respect to its features and it supports the OTEL related integrations which helps us to adopt the updations of Otel very easily and also it gives us flexible to drop the data in different stages through the …
Its covers all the observability aspects as well as giving us more competitive pricing models compared to other providers that's why I like to use New Relic in place of other tools. And also it introduces new Agentic AI features as well as it adopts AI in its RCA. As an …
Tracing of the services calls between the entire components in the architecture is good and easy to understand. Dashboarding building process is simple. UI is simple.
New Relic stood out to us primarily because of its all-in one approach, combining APM, infra monitoring, logs and alerts in single platform. Compared to other tools we evaluated, if offered a smoother on boarding experience and required less stitching together of different …
The New Relic Platform addresses this challenge with the new plugin architecture. Plugins provide a way to monitor each of these technologies, extending the New Relic interface with custom-made dashboards specific to each. They pair the reporting of metrics specific to the …
New Relic is the most full-featured offering that we've found, and is incredibly easy to start using with a PHP app. The New Relic agent is installed as a PHP extension so it is able to monitor and track the performance of any PHP app being run by the web server. Other tools …
New Relic has been DevOps and Developer friendly to onboard and use. Also pricing-wise, it is one of the best in terms of ROI. There are few features better in other APM solutions but New Relic is working on new features faster recently.
New Relic has a native integration with the IaaS service that the company utilizes which made it very easy to set up, integrate, and it also has consolidated billing with that IaaS service which is a big plus for the organization. After evaluating, I also thought it had the …
We selected New Relic since it was very dynamic and versatile to use. It works well in all aspects of monitoring, and observability and would allow having a focus on collaboration with different repeatable processes. Also, New Relic has a good focus on working well with CLI, …
The differentiating feature, in my opinion, is the support given by New Relic, in our org, there is a slack channel dedicated for New Relic which allows us to have a quicker response and more convenience.
Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
Firebase should be your first choice if your platform is mobile first. Firebase's mobile platform support for client-side applications is second to none, and I cannot think of a comparable cross-platform toolkit. Firebase also integrates well with your server-side solution, meaning that you can plug Firebase into your existing app architecture with minimal effort.
Firebase lags behind on the desktop, however. Although macOS support is rapidly catching up, full Windows support is a glaring omission for most Firebase features. This means that if your platform targets Windows, you will need to implement the client functionality manually using Firebase's web APIs and wrappers, or look for another solution.
New Relic its an excellent tool for monitoring services used on the SAAS universe, like web servers, relational and nosql dbms, reverse proxies, text databases, etc. Its also a powerful tool to monitor resource usage on said servers. However, its not well fitted to monitor custom services - if you need to generate alerts based on logs or database information, for example
The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
Analytics wise, retention is extremely important to our app, therefore we take advantage of the cohort analysis to see the impact of our middle funnel (retargeting, push, email) efforts affect the percent of users that come back into the app. Firebase allows us to easily segment these this data and look at a running average based on certain dates.
When it comes to any mobile app, a deep linking strategy is essential to any apps success. With Firebase's Dynamic Links, we are able to share dynamic links (recognize user device) that are able to redirect to in-app content. These deep links allow users to share other deep-linked content with friends, that also have link preview assets.
Firebase allows users to effectively track events, funnels, and MAUs. With this simple event tracking feature, users can put organize these events into funnels of their main user flows (e.g., checkout flows, onboarding flows, etc.), and subsequently be able to understand where the drop-off is in the funnel and then prioritize areas of the funnel to fix. Also, MAU is important to be able to tell if you are bringing in new users and what's the active volume for each platform (Android, iOS).
Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
I would appreciate more supportive examples for how to filter and view metrics in the explorer
I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Attribution and specifically multi-touch attribution could be more robust such as Branch or Appsflyer but understand this isn't Firebases bread and butter.
More parameters. Firebase allows you to track tons of events (believe it's up to 50 or so) but the parameters of the events it only allows you to track 5 which is so messily and unbelievable. So you're able to get good high-level data but if you want to get granular with the events and actions are taken on your app to get real data insight you either have to go with a paid data analytics platform or bring on someone that's an expert in SQL to go through Big Query.
City-specific data instead of just country-specific data would have been a huge plus as well.
And while powerful, building tailored dashboards with organ-specific metrics (such as energy load variance across regions) can be difficult to navigate. The UI isn't as drag-and-drop easy, and query-based widgets typically involve some trial and error for non-devs.
Alerts may be hypersensitive or over general. I We often get a spam of non-critical alerts while doing load testing, all overhauling to me alone and making it difficult to identify actual issues especially in energy systems where spikes are very common.
With our expanding fleet of Iot devices, the per-host pricing model is becoming expensive, quickly. More detailed billing based on microservices, or that works at sensor level, would make it more adaptable for energy platforms.
The only issue that we have had with New Relic is that the price might be a little expensive for smaller companies. The amount of data you store in New Relic impacts the cost, and can get away from you if you don't work closely with the vendor. Overall though the application is top notch.
There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
I don't use the Firebase UI much, but rather connect it to GA4. GA4 has a great event model but the GA4 UI and analysis capabilities are limited. It's harder to measure product usage type of engagement but if you have the time and resources to leverage the GA4 to BiqQuery export you'll have all the raw event data you'll need for deep analysis, segmentation, and audience activation.
I have given this much rating as I am used New Relic in different sectors and for different use cases like its K8s monitoring, infra monitoring, full stack monitoring as compare to other tools New Relic gives data in a formatted and connected way, and also it is giving us value for money. It also launches new features day by day which helps users to track the issue very quickly. It also supports OTel integrations which is the latest trend of observability tools. thats why I had given this much rating to New Relic.
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
Our analytics folks handled the majority of the communication when it came to customer service, but as far as I was aware, the support we got was pretty good. When we had an issue, we were able to reach out and get support in a timely fashion. Firebase was easy to reach and reasonably available to assist when needed.
The support team has been really helpful and resolved most of the issues on time. However, for a couple of issues, several follow-ups were needed to elicit a reasonable response. The issue was deeply technical and could have been investigated only by their Architects, and bringing them into the ticket took longer than needed
It's better to start by implementing New Relic in one project and test everything. Try to follow best recommended practices and read all the official documentation. Everything seems well tested. Then, start by installing agents to the rest of your projects and keep a close look to all logs and metrics New Relic gives you.
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.
Key features:
Logs, metrics, and APM (Application Performance Monitoring)
Real-time alerting and dashboards
Supports Kubernetes, AWS, GCP, and other integrations
RUM (Real User Monitoring) and Synthetics
✅ Best for backend, server, and distributed systems monitoring.
Before using Firebase, we exclusively used self hosted database services. Using Firebase has allowed us to reduce reliance on single points of failure and systems that are difficult to scale. Additionally, Firebase is much easier to set up and use than any sort of self hosted database. This simplicity has allowed us to try features that we might not have based on the amount of work they required in the past.
Data Dog has solutions that look more attractive, but not at their price point. We have also tried to build a solution straight from the Cloud, where our business is built, but some things are too hard to replicate. This shows that New Relic is useful and helps our efficiency.
Makes building real-time interfaces easy to do at scale with no backend involvement.
Very low pricing for small companies and green-fields projects.
Lack of support for more complicated queries needs to be managed by users and often forces strange architecture choices for data to enable it to be easily accessed.